The spatial–temporal variability of methane emissions in a montane headstream: implication of precipitation, morphology and microhabitat

Headstreams are significant sources of atmospheric methane (CH₄). However, the high spatial–temporal variability presents significant challenges for inventory estimation of CH₄ emissions from headstreams. Particularly in mountainous headstreams with high heterogeneity of morphology and microhabitats, the key factors controlling CH₄ emissions remain unclear. This study conducted monthly surveys of dissolved CH₄ concentration (dCH₄) and CH₄ flux (fCH₄) in a montane headstream basin in southwestern China at high spatial resolution. It focused on the synthetic effects of morphology, microhabitat, and nutrients on the spatial–temporal variability in CH₄ fluxes. The overall mean dCH₄ and fCH₄ in the selected headstream were 79.4 ± 80.4 nmol L^-1 and 1.24 ± 0.98 mmol m⁻² d^-1, respectively, indicating it acts as a moderate source of CH₄ emission. The dCH₄ and fCH₄ displayed opposite temporal patterns: high concentrations but low fluxes during the dry season, and low concentrations but high fluxes during the wet season. These temporal patterns are primarily dominated by enhanced turbulent degassing driven by seasonal precipitation. From a watershed perspective, both dCH₄ and fCH₄ increased progressively from upstream to downstream. Total carbon and organic carbon in waters can explain over 60 % of the spatial variation in fCH₄ either in dry or rainy seasons, indicating that carbon accumulation downstream may account for the watershed variation in CH₄ emissions. River width and slope can influence dCH₄ and fCH₄ indirectly via disturbing nutrient distribution. In addition, from a local perspective, microhabitats (deep pools, shallows, or rapids) and substrate types in the headstream intensified the local heterogeneity of fCH₄ by affecting water turbulence and nutrient distribution, leading to multiple spatial variations. Given the complex habitat conditions of mountainous streams, especially in the context of global climate change, incorporating these variables into future models will enhance our understanding of the roles of headstreams in the global carbon cycle.